1. Baldassarre, G., Mirolli, M.: Intrinsically Motivated Learning in Natural and Artificial Systems. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-32375-1
2. Barto, A.G., Mahadevan, S.: Recent advances in hierarchical reinforcement learning. Disc. Event Dyn. Syst. 13(1), 41–77 (2003)
3. Bellemare, M., Srinivasan, S., Ostrovski, G., Schaul, T., Saxton, D., Munos, R.: Unifying count-based exploration and intrinsic motivation. Adv. Neural Inf. Process. Syst. 29 (2016)
4. Bengio, Y., Louradour, J., Collobert, R., Weston, J.: Curriculum learning. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 41–48 (2009)
5. Blaes, S., Vlastelica Pogančić, M., Zhu, J., Martius, G.: Control what you can: intrinsically motivated task-planning agent. Adv. Neural Inf. Process. Syst. 32 (2019)